Memory-Efficient Training for Fully Unrolled Deep Learned PET Image Reconstruction with Iteration-Dependent Targets

We propose a new version of the forward-backward splitting expectation-maximisation network (FBSEM-Net) along with a new memory-efficient training method enabling the training of fully unrolled implementations of 3D FBSEM-Net. FBSEM-Net unfolds the maximum a posteriori expectation-maximisation algorithm and replaces the regularisation step by a residual convolutional neural network. Both the gradient of the prior and the regularisation strength are learned from training data. In this new implementation, three modifications of the original framework are included. First, iteration-dependent networks are used to have a customised regularisation at each iteration. Second, iteration-dependent targets and losses are introduced so that the regularised reconstruction matches the reconstruction of noise-free data at every iteration. Third, sequential training is performed, making training of large unrolled networks far more memory efficient and feasible. Since sequential training permits unrolling a high number of iterations, there is no need for artificial use of the regularisation step as a leapfrogging acceleration. The results obtained on 2D and 3D simulated data show that FBSEM-Net using iteration-dependent targets and losses improves the consistency in the optimisation of the network parameters over different training runs. We also found that using iteration-dependent targets increases the generalisation capabilities of the network. Furthermore, unrolled networks using iteration-dependent regularisation allowed a slight reduction in reconstruction error compared to using a fixed regularisation network at each iteration. Finally, we demonstrate that sequential training successfully addresses potentially serious memory issues during the training of deep unrolled networks. In particular, it enables the training of 3D fully unrolled FBSEM-Net, not previously feasible, by reducing the memory usage by up to 98% compared to a conventional end-to-end training. We also note that the truncation of the backpropagation (due to sequential training) does not notably impact the network’s performance compared to conventional training with a full backpropagation through the entire network

Argumentaire pour une utilisation plus large de la photochimiothérapie extracorporelle chez l’enfant

International audienceThe management of immune diseases in children remains challenging , although significant advances have been made. In addition to pharmacological approaches, extracorporeal photochemotherapy (ECP) is distinctive in its ability to provide immunomodulation without immune suppression or toxicity. However, in practice, this therapy is not widely used because of logistical issues and the lack of robust clinical pediatric studies. Here, we discuss the potential clinical applications of ECP in children and emphasize the need for a rigorous and specifically pediatric clinical evaluation of ECP. ß 2010 Elsevier Masson SAS. All rights reserved. Résumé Malgré l'apport des biothérapies, le traitement des maladies dysim-munitaires sévères et des conflits allogéniques de l'enfant reste difficile et entaché de nombreuses complications. Dans ce contexte, la photo-chimiothérapie extracorporelle (PCE) (thérapie cellulaire qui repose sur l'effet immunomodulateur des cellules mononucléées du patient, prélevées par aphérèse et exposées ex vivo aux rayons ultraviolets A [UVA] en présence de psoralène) a l'avantage notable d'induire une tolérance immunitaire sans générer d'immunosuppression systémique ni de toxicité a ` court, moyen ou long terme. Cette immunomodulation fait intervenir notamment la génération de lymphocytes T régulateurs (T reg). Malgré cela, la PCE est peu utilisée en raison de ses contraintes logistiques et du manque de données cliniques. Nous proposons une revue des indications reconnues et potentielles de la PCE en pédiatrie. Nous insistons sur la nécessité d'une e ´valuation clinique spécifique a ` l'enfant qui ne peut se concevoir sans la participation active des cliniciens pédiatres en particulier dans le domaine de la transplanta-tion et des maladies auto-immunes et inflammatoires

Rapid Desensitization to Adalimumab Is Associated With Decreased Basophil Sensitivity

International audienc

Radiothérapie interne du mélanome métastatique par [131I]ICF01012 : phase I

International audienc

A chemogenomic approach to identify personalized therapy for patients with relapse or refractory acute myeloid leukemia: results of a prospective feasibility study

International audienceTargeted next-generation sequencing (tNGS) and ex vivo drug sensitivity/resistance profiling (DSRP) have laid foundations defining the functional genomic landscape of acute myeloid leukemia (AML) and premises of personalized medicine to guide treatment options for patients with aggressive and/or chemorefractory hematological malignancies. Here, we have assessed the feasibility of a tailored treatment strategy (TTS) guided by systematic parallel ex vivo DSRP and tNGS for patients with relapsed/refractory AML (number NCT02619071). A TTS issued by an institutional personalized committee could be achieved for 47/55 included patients (85%), 5 based on tNGS only, 6 on DSRP only, while 36 could be proposed on the basis of both, yielding more options and a better rationale. The TSS was available in <21 days for 28 patients (58.3%). On average, 3 to 4 potentially active drugs were selected per patient with only five patient samples being resistant to the entire drug panel. Seventeen patients received a TTS-guided treatment, resulting in four complete remissions, one partial remission, and five decreased peripheral blast counts. Our results show that chemogenomic combining tNGS with DSRP to determine a TTS is a promising approach to propose patient-specific treatment options within 21 days